Quick Answer: Yes, DeepSeek Can Generate Images
Yes, DeepSeek can generate images through its advanced Janus Pro model series, which represents a breakthrough in AI image generation technology. The Janus Pro model, particularly the 7-billion parameter version (Janus Pro-7B), offers state-of-the-art image generation capabilities that can transform text descriptions into high-quality visuals. DeepSeek’s Janus Pro achieved 80% overall accuracy in text-to-image tasks, compared to 67% for DALL-E 3 and 74% for Stable Diffusion, setting new benchmarks with 99% single-object accuracy and 90% positional alignment.
The Chinese AI company launched its image generation model in January 2025, making it freely available to users worldwide under an MIT license. This breakthrough positions DeepSeek as a serious competitor to established players like OpenAI’s DALL-E 3, Adobe Firefly, and Stability AI’s Stable Diffusion.
What is DeepSeek?
DeepSeek is a Chinese AI startup founded in 2023 in Hangzhou, China, by Liang Wenfeng, who previously co-founded one of China’s top hedge funds, High-Flyer, which focuses on AI-driven quantitative trading. Unlike most Chinese AI firms, DeepSeek operates independently of major tech giants such as Baidu and Alibaba, with Liang’s motivation rooted in scientific curiosity rather than immediate financial returns.
The company emerged from Fire-Flyer, a deep-learning branch of High-Flyer hedge fund, and has quickly gained global recognition for developing cost-efficient AI models that rival American competitors. DeepSeek was founded as a research lab dedicated to pursuing Artificial General Intelligence (AGI), with Liang reportedly hiring young computer science researchers with a pitch to “solve the hardest questions in the world” without aiming for profits.
What makes DeepSeek particularly noteworthy is its approach to AI development. The company said it had spent just $5.6 million powering its base AI model, compared with the hundreds of millions, if not billions of dollars US companies spend on their AI technologies. This achievement is especially remarkable considering the US restrictions on high-performance AI chips to China.
DeepSeek’s Image Generation Technology: Janus Pro Explained
The Janus Pro Architecture
DeepSeek’s image generation capabilities are powered by the Janus Pro model series, which features decoupled visual encoding pathways with unified transformer processing for enhanced flexibility and performance. One of the standout features of Janus-Pro is that it doesn’t use a single system to handle both interpreting and creating visuals. Instead, it separates these processes through decoupled visual encoding.
This innovative approach allows the model to:
- Use specialized pathways for understanding existing images
- Employ different systems for generating new images from text descriptions
- Maintain superior performance in both understanding and generation tasks
Available Model Versions
Janus Pro is available in two main versions: Janus Pro-7B (7 billion parameters) and Janus Pro-1B (1.5 billion parameters). Both versions are part of the Janus AI ecosystem and are open-source under the MIT license, making them accessible for both research and commercial applications.
The larger 7B model offers superior performance and has been the focus of benchmark comparisons with industry leaders like DALL-E 3 and Stable Diffusion.
Technical Specifications
For multimodal understanding, Janus Pro uses the SigLIP-L as the vision encoder, which supports 384 x 384 image input. For image generation, it uses a tokenizer with a downsample rate of 16. The model leverages an autoregressive framework for multimodal understanding and image generation, featuring a split visual encoding system and a unified transformer architecture, aiming for efficiency in processing.
How DeepSeek’s Image Generation Compares to Competitors
Benchmark Performance
DeepSeek’s Janus Pro has demonstrated impressive performance across multiple evaluation metrics:
GenEval Benchmark Results: Janus Pro achieved 80% overall accuracy in text-to-image tasks, compared to 67% for DALL-E 3 and 74% for Stable Diffusion. The model also set new benchmarks with 99% single-object accuracy and 90% positional alignment.
DPG-Bench Performance: On DPG-Bench, which tests accuracy on detailed prompt execution, Janus-Pro-7B scores 84.2%, surpassing all other models.
Strengths and Limitations
Strengths:
- Better at creating realistic images with superior color and positional alignment tasks
- Achieved more visually appealing and stable image outputs by adding 72 million high-quality synthetic images and balancing them with real-world data
- Cost-effective training and operation
- Open-source availability
Limitations:
- Struggles significantly with generating humans, particularly with hands and facial structures
- Falls behind other image generation models in photorealistic imagery and complex facial compositions
- Limited resolution capabilities for fine detail restoration
How to Access and Use DeepSeek for Image Generation
Getting Started
The fastest way to test Janus-Pro is through its Hugging Face Spaces demo, where you can enter prompts and generate text or images directly in your browser. This requires no installation or setup.
Users can access DeepSeek’s image generation capabilities through several methods:
- Hugging Face Platform: Direct browser-based access for immediate testing
- Official Website: Available through DeepSeek’s dedicated image generation portal
- Local Deployment: For developers wanting to integrate the technology into their own applications
- API Access: Though not officially released, developers can deploy it on their own servers
Usage Process
The image generation process with DeepSeek follows a straightforward workflow:
- Input Text Prompt: Provide a detailed description of the image you want to generate
- Style Selection: Choose from various artistic styles and fine-tune settings
- Generate: Click the generate button and watch DeepSeek create your vision
- Download: Save your generated image for use in your projects
DeepSeek can generate a wide variety of images, from stunning landscapes to photorealistic portraits and abstract art, allowing users to create anything their imagination desires.
Commercial Use and Licensing
Since Janus Pro is released under an MIT license, you can use it for commercial applications without restrictions. However, it’s recommended to check the terms of use to ensure compliance with any additional requirements.
This open-source approach makes DeepSeek particularly attractive for:
- Businesses looking for cost-effective image generation solutions
- Developers wanting to integrate AI image generation into their applications
- Researchers studying multimodal AI capabilities
- Content creators seeking affordable alternatives to premium AI image services
Market Impact and Industry Reception
Stock Market Response
DeepSeek’s breakthrough in image generation, combined with its other AI models, has had significant market implications. Market analysts speculate that investors are reacting to DeepSeek researchers’ claim that they built their models without expensive GPUs, at a cost of under $6 million, raising concerns over the future demand for high-end AI chips.
Industry Recognition
DeepSeek’s new open-source AI model surpassed Stability AI and Microsoft-backed OpenAI’s models in benchmarks for image generation, according to the Chinese startup’s technical report. This achievement has garnered attention from major tech figures and prompted discussions about the competitive landscape in AI development.
Expert Opinions
Tech industry observers have noted the significance of DeepSeek’s achievements. Venture capitalist Marc Andreessen called DeepSeek R1 “AI’s Sputnik moment” in a post on social platform X, referencing the 1957 satellite launch that set off a Cold War space exploration race between the Soviet Union and the U.S.
Future Developments and Roadmap
DeepSeek continues to innovate in the AI space, with regular updates and improvements to their models. The company maintains a 72-hour knowledge update cycle, 12 times faster than traditional quarterly updates, ensuring their models stay current with the latest developments.
The company’s commitment to open-source development means that researchers and developers worldwide can contribute to and benefit from ongoing improvements to the image generation technology.
Applications and Use Cases
DeepSeek’s image generation capabilities serve multiple industries and use cases:
Creative Industries:
- Digital art creation and concept visualization
- Marketing material development
- Social media content generation
- Game design and environment creation
Business Applications:
- Product mockup generation
- Advertising visual creation
- E-commerce product imagery
- Brand asset development
Educational and Research:
- Academic research into multimodal AI
- Educational content creation
- Scientific visualization
- Training data generation for other AI models
Comparison with Other AI Image Generators
When choosing between DeepSeek’s Janus Pro and other AI image generators, consider these factors:
DeepSeek Janus Pro vs. DALL-E 3:
- DeepSeek excels in benchmark performance and cost efficiency
- DALL-E 3 has superior human figure generation and integration with ChatGPT
- DeepSeek is open-source; DALL-E 3 is proprietary
DeepSeek Janus Pro vs. Stable Diffusion:
- Both are open-source with active communities
- DeepSeek shows better instruction-following capabilities
- Stable Diffusion has a more mature ecosystem and plugins
DeepSeek Janus Pro vs. Midjourney:
- Midjourney focuses on artistic and stylized images
- DeepSeek emphasizes realistic and prompt-accurate generation
- Different pricing models and accessibility options